title: Tracking non-stationary spectral peak structure in EEG data.
abstract: We develop a particle filter algorithm to simultaneously estimate and track the instantaneous peak frequency, amplitude, and bandwidth of multiple concurrent non-stationary components of an EEG signal in the time-frequency domain. We use this method to characterize human EEG activity during anesthesia-induced unconsciousness.
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Prerau
authors.forename: Patrick L
authors.initials: PL
authors.lastname: Purdon
authors.forename: Uri T
authors.initials: UT
authors.lastname: Eden
mesh_terms: D000465:Algorithms; D000758:Anesthesia / Q000379:methods*; D001499:Bayes Theorem; D003198:Computer Simulation; D004569:Electroencephalography / Q000379:methods*; D006801:Humans; D009415:Nerve Net; D016011:Normal Distribution; D012815:Signal Processing, Computer-Assisted; D013997:Time Factors